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Changes of Translation Definition and Turns of Translation Studies

2012· article· en· W2158267232 on OpenAlexvenueno aff
Jixing Long

Bibliographic record

VenueCross-cultural communication · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsTranslation studiesPerspective (graphical)Translation (biology)Dynamic and formal equivalenceScope (computer science)Paradigm shiftComputer scienceEpistemologyLinguisticsArtificial intelligenceMachine translationPhilosophy

Abstract

fetched live from OpenAlex

Since the twentieth century, translation studies has made great progress. The study of translation ushers one turn after another. Throughout the recent history of translation studies, few scholars review the appearance of the turns from the perspective of translation definition. From the academic perspective and on the basis of Thomas Samuel Kuhn’s paradigm theory, this article discusses the relationships between the changing definitions of translation and the turns of translation studies. It chooses the definitions of translation proposed by the most famous theorists to analyze. And, the mainly two turns and the new trend of contemporary translation studies are attributed into three paradigms (linguistic paradigm, cultural paradigm, and social and psychological paradigm) to discuss. By a careful research, the article comes to a conclusion that the changes of definitions and the turns of translation studies affect and contact each other closely. The definition of translation determines the scope of translation studies. A new definition that is widely accepted always generates a new turn and the new turn tends to breed a next new definition, and so on and so forth, hence the development of translation studies. Key words: Definition of translation; Translation studies; Paradigm; Paradigm shift; Turn

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.278
GPT teacher head0.393
Teacher spread0.115 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2012
Admission routes1
Has abstractyes

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